Year: 2024
Type: article
Abstract: This paper examines the role of Artificial Intelligence (AI) in transforming global health surveillance systems, emphasizing its profound impact on disease detection, monitoring, and response capabilities. By leveraging advanced AI technologies such as machine learning and natural language processing, the paper delves into how these tools enhance the efficiency and accuracy of public health strategies. Through a series of case studies, the effectiveness of AI in real-world scenarios is analyzed, showcasing its potential to predict and manage disease outbreaks more effectively than traditional methods. Additionally, the paper addresses the ethical challenges and technical limitations of integrating AI into existing health surveillance frameworks. Recommendations for overcoming these challenges are provided, alongside a discussion on the necessity of robust data protection measures and the development of unbiased AI algorithms. The comprehensive analysis aims to provide stakeholders with insights into both the transformative potential of AI and the pragmatic considerations needed for its responsible implementation in the field of global health surveillance.
Author: TOPEOLA BALKIS AWOFALA
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4404641518